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Record W7132924040

Parallels and Peculiarities: Investigating Concussion and Mental Health Symptoms Using Neuropsychology and Neuroimaging in Pediatric Populations

2024· dissertation· W7132924040 on OpenAlexaff
Elena Sheldrake

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsConcussionNeuroimagingMental healthNeuropsychologyAnxietyPoison controlInjury preventionCognition
DOInot available

Abstract

fetched live from OpenAlex

Youth who sustain a concussion are at risk of experiencing persistent post-concussion symptoms (PPCS). As youth are at a period of developmental neuroplasticity, PPCS leaves them vulnerable to academic, personal, and social impacts. Despite the variety of symptoms experienced between individuals, mental health symptoms (e.g., anxiety and depression) are commonly reported and trend upwards annually. While there appears to a relationship between PPCS and mental health symptoms, the exact mechanisms are still unknown. Currently, PPCS diagnosis relies on clinical history and self-report, and lacks concrete neuroimaging biomarkers. Such indicators may provide objective identifiers generalizable to those with concussion, and may characterize and distinguish concussion from mental health symptoms. Therefore, the motivation of this thesis is to better characterize concussion (and PPCS) in youth using neuroimaging methods and neuropsychological outcomes. This motivation grounded the three primary objectives of this thesis: (1) to synthesize the existing literature surrounding (a) PPCS and mental health outcomes across the lifespan (Chapter 2), and (b) trends and patterns of PPCS and MRI modalities in pediatric populations (Chapter 3); (2) to use an established open-access database to characterize youth with concussion using frontoparietal network and amygdala (FPN-amygdala) functional connectivity (via resting-state fMRI) and emotional and behavioural profiles compared to youth with anxiety, and age-and-sex matched youth (Chapter 4); and (3) to use a pilot dataset of youth experiencing PPCS to explore potential relationships between functional neuroimaging (FPN) and neuropsychological outcomes (cognitive, emotional, behavioural) (Chapter 5). Research syntheses (Chapters 2 and 3) highlighted the need for more concussion studies focusing on pediatric populations and mental health symptoms, especially anxiety, and the heterogeneity in MRI modalities and results. Data-driven studies revealed significant brain disruptions in the FPN-amygdala in youth with concussion (Chapter 4), and a significant relationship between verbal learning and FPN connectivity in youth with PPCS (Chapter 5). This thesis identified significant brain disruptions that can be used as building blocks in future concussion research to identify objective indicators of PPCS. Such indicators can inform clinical decision-making and may help to distinguish and subsequently mitigate mental health symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.113
GPT teacher head0.461
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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